Research on CO2 transfer in basalt and sandstone using 3D pore space model generation and mathematical morphology
Introduction
Thermal power plant is the main power generation mode which produces about 85% of the world's electricity. It is impossible to totally replace the burning fossil fuels with clean energy that does not directly produce CO2 in the short term (Wilberforce et al., 2019). As the most important environmental governance strategy, CO2 capture and storage (CCS) technology was highlighted at the 21st Conference of the Parties (COP21) (Bui et al., 2018). Underground CO2 storage is a permanent solution to alleviating emissions in the atmosphere and reducing the greenhouse effect (Oelkers et al., 2008; Wells et al., 2017; Schwartz, 2020). Approximately 8% of the world's continents and the majority of the seafloor are made of basalt, and these basalt layers have a huge potential for CO2 storage (McGrail et al., 2006; Rosenbauer et al., 2012; Gislason et al., 2014; Snæbjörnsdóttir et al., 2020). When CO2 is injected into active basalt, H2CO3 reacts with the divalent metal cations (Fe2+, Ca2+, and Mg2+) in the rock and solidifies, becoming part of basalt and thus is permanently stored (Matter et al., 2014; Snæbjörnsdóttir et al., 2014; Sigfusson et al., 2015; Snæbjörnsdóttir and Gislason, 2016):
Besides the basalt layer, the deep saline aquifers of sandstone are also suitable CO2 geological storage area (Xie and Economides, 2009; Varre et al., 2015). The Illinois State Geological Survey (ISGS) in USA conducted CO2 injection experiments on Mt. Simon sandstone in Decatur area, and determined its feasibility for CO2 solidification (Kohanpur et al., 2020). The Shenhua Carbon Capture and Storage (Shenhua CCS) project in China also performed CO2 injection into Liujiagou sandstone layer, and achieved excellent storage effects (Ning et al., 2014).
As the basis for CO2 migration, the three-dimensional pore network of rock affects the feasibility and efficiency of CO2 solidification and storage. The connectivity of the pore space is the main factor. In order to conduct an in-depth study of this issue, scholars have used scanning techniques such as the micro-computed tomography (Micro-CT) to detect the real pore microstructure of rock (Xiong et al., 2018; Callow et al., 2018; Becker et al., 2019). Although direct imaging technology possesses the advantage of presenting the true morphology of material's microstructure, the selection of sample, observing preparation and scanning operation may bring inaccuracies. In particular, reliable and representative 3D photos with high resolution and sufficient scanning voxel size to comprise the whole range of pore size often lead to expensive cost and long duration experiment. Considering this, it is indispensable to reconstruct multi-scale digital models of rock based on the characteristic parameters of pore space (Joekar-Niasar and Hassanizadeh, 2012; Nomeli et al., 2014; Zhu et al., 2019). Traditional modeling methods of porous media usually define pores as simple elements with specific shapes, such as cylinders (Ranaivomanana et al., 2011) and spherical elements (Varloteaux et al., 2013). For instance, in recent years, Arshadi et al. (2020) used circular, triangular and rectangular cross-section forms to establish the pore network model of arkose. Kohanpur et al. (2020) used the maximal ball (MB) algorithm to equate pores in heterogeneous sandstone to spheres to study the two-phase flow of CO2-brine. Song et al. (2019) used Avizo to equate pores to spheres to evaluate the permeability of rock. These methods gave us new ideas to investigate the microstructure and the related properties, but they are always based on the simplification of pore shape, thus are not able to present the actual randomness of pore form and spatial distribution.
Based on above considerations, in this study, the biphasic change on continuous Gaussian random field was numerically realized to generate the 3D porous model that satisfies the porosity and the pore size distribution of the studied rock. This method does not rely on an initial setting of pore shape and can present the random morphology of pore network. After finishing the model generation, numerical calculation scenarios based on the image analysis method of mathematical morphology were designed and applied to extract the potential gas transfer paths, to analyze the morphological characteristics (connectivity, tortuosity, pore throat, etc.) and thus to evaluate the CO2 storage performance.
Section snippets
Porous model generation and validation
This part introduces the 3D porous model generation and validation. The main research methods include the biphasic change on continuous Gaussian random field, the combination of biphasic fields and the image analysis method of mathematical morphology.
Results and discussion
The numerical investigation of CO2 transfer in basalt and sandstone is performed in two steps: (1). Rock model generation and validation. The main methods are the biphasic change on Gaussian random field, the combination of biphasic fields and the model validation based on morphological opening; (2). CO2 transfer paths analysis. The proposed calculation scenario based on geodesic reconstruction is applied on the validated basalt and sandstone models to predict the gas transfer properties.
Conclusions
In order to investigate the CO2 transfer in basalt and sandstone, the 3D rock models were generated based on the biphasic change on continuous random field. By varying the threshold and the correlation length of the initial Gaussian random field, the biphasic field is capable of representing diverse kinds of porous media. The combination of biphasic fields provides a randomly formed pore space, and meanwhile satisfies the porosity and the pore size distribution of the studied material.
Several
Code availability section
The code name is “RockModel-Build-and-Analyze”. The Code is written in C++ and is developed and maintained by Dr. Xiang ZHANG. His email address is [email protected]. The code is released in October 2021. A PC with 3.4 GHz processor and 16 GB Ram is able to run the code. It can be downloaded from Github (https://github.com/magiczx1989/RockModel-Build-and-Analyze).
Authorship contribution statement
Xiang Zhang: Conceptualization (lead); Methodology (lead); Investigation (lead); Software (lead); Writing - Original Draft (lead); Writing - Review and Editing (equal); Shuming Liu: Conceptualization (supporting); Methodology (supporting); Software (supporting); Supervision (lead); Writing - Original Draft (supporting); Writing - Review and Editing (equal); Zhen Lei: Methodology (supporting); Software (supporting); Supervision (supporting); Writing - Review and Editing (equal); Juntong Qu:
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
The authors are grateful to the Applied Basic Research Foundation of Yunnan Province [grant No. 2019FD125], the Yunnan Provincial Department of Education Science Research Fund Project [grant No. 2019J0024] and [grant No. 2021Y015] for funding this work in study design, in analysis and interpretation of data and in the decision to submit the article for publication.
References (35)
- et al.
Multidimensional reactive transport modeling of CO2 mineral sequestration in basalts at the Hellisheidi geothermal field, Iceland
Int. J. Greenh. Gas Control
(2012) - et al.
Impact of mineralogy and wettability on pore-scale displacement of NAPLs in heterogeneous porous media
J. Contam. Hydrol.
(2020) - et al.
Assessing the carbon sequestration potential of basalt using X-ray micro-CT and rock mechanics
Int. J. Greenh. Gas Control
(2018) - et al.
Rapid solubility and mineral storage of CO2 in basalt
Energy Proc.
(2014) - et al.
Two-phase flow of CO2-brine in a heterogeneous sandstone: characterization of the rock and comparison of the lattice-Boltzmann, pore-network, and direct numerical simulation methods
Adv. Water Resour.
(2020) - et al.
Monitoring permanent CO2 storage by in situ mineral carbonation using a reactive tracer technique
Energy Proc.
(2014) - et al.
A new model for the density of saturated solutions of CO2–H2O–NaCl in saline aquifers
Int. J. Greenh. Gas Control
(2014) - et al.
Toward a better comprehension and modeling of hysteresis cycles in the water sorption–desorption process for cement based materials
Cement Concr. Res.
(2011) - et al.
Carbon sequestration via reaction with basaltic rocks: geochemical modeling and experimental results
Geochem. Cosmochim. Acta
(2012) - et al.
Solving the carbon-dioxide buoyancy challenge: the design and field testing of a dissolved CO2 injection system
Int. J. Greenh. Gas Control
(2015)
Storage potential of basaltic rocks in Iceland and the oceanic ridges
Energy Proc.
CO2 storage potential of basaltic rocks offshore Iceland
Energy Proc.
Pore network modelling to determine the transport properties in presence of a reactive fluid: from pore to reservoir scale
Adv. Water Resour.
Influence of geochemical processes on the geomechanical response of the overburden due to CO2 storage in saline aquifers
Int. J. Greenh. Gas Control
Dissolution and surface roughening of Columbia River flood basalt at geologic carbon sequestration conditions
Chem. Geol.
Outlook of carbon capture technology and challenges
Sci. Total Environ.
The impact of carbon geological sequestration
J. Nat. Gas Sci. Eng.
Cited by (2)
Micro-CT characterization on pore structure evolution of low-permeability sandstone under acid treatment
2023, Applied GeochemistryExperimental and Numerical Research on Water Transport during Adsorption and Desorption in Cement-Based Materials
2023, CMES - Computer Modeling in Engineering and Sciences